get GNU

A list of lists

Let’s start with a simple example of converting [[0,1], [2,3]] into [0,1,2,3]. This type of flattening is called shallow flattening as it will only flatten lists of one level depth.

Using list comprehension

List comprehension is a way to create lists in one line of code. Let’s see how we can use list comprehension for flattening the lists.

flatten_list = [item for subl in l for item in subl]

Let’s break this line of code.

The first loop is “for subl in l” and the second nested loop is “ for item in subl ”.

Deep flattening

When we will try to flatten a list of varying depth like this [ [ 0, 1 ], [ [ 2 ] ][ 3, 4 ] ] list with shallow flattening, the output will be as follows:

But our goal is to convert [ [ 0, 1 ], [ [ 2 ] ], [ 3, 4 ] ] this list to this [ 0, 1, 2, 3, 4 ] list. This problem can be solved with deep flattening. In deep flattening, the process undergoes multiple levels of depths to create a flattened list.

There is a built-in function named deepflatten in the iteration_utilities library. You need to install this library using.

We have successfully achieved our target. Let’s take another example by changing the depth of the list.

Using recursion

To flatten a list recursively, we will call the function inside itself to run until the end:

Check whether the list length is equal to 1. If true, then check whether the type of the first index of the list is a “list”.if true, then call the function that flattens the list else, store the number in the result.

The function will be like this:

When we run this code against this [[0,1], [2], [3,4]] list, the results will be:

Flatten without recursion

To flatten a list without recursion, we will use a while loop until we pop all the elements from it. Take a look at the code, you will have a better understanding:

Flatten nested lists

To flatten a nested list, you can use deep flattening. For deep flattening lists within lists, use the given below code:

Also, you can use the recursive function as we did above.

A list of tuples

Flattening a list of tuples of a single depth is the same as flattening lists within lists. For shallow flattening of tuples, use the following code:

For deep flattening, a list of tuples with varying depth (nested), you can use the code given below:

Flatten 2d array

Let’s take a 2d array of 5×5 dimensions and convert it to a flattened list. Check the following code:

A list of NumPy arrays

There are three built-in functions defined in NumPy library that can convert the NumPy array into flattened lists.

numpy.ravel()

numpy.flatten()

numpy.reshape(-1)

numpy.ravel()

numpy.flatten()

numpy.reshape(-1)

The difference between these three functions is speed. The flatten function returns a copy every time it flattens the array. So, if you have a large data set, don’t use the flatten function; it’s the slower one.

Flatten JSON objects

For flattening JSON objects, there is a built-in function in the flatten_json library named flatten().

You first need to install it using pip:

pip install flatten_json

Then you can use this function in our code:

Flatten a list of objects

You can flatten a list of objects using a built-in function available in the itertools library with function name itertools.chain.from_iterable() Let’s see how to use this function:

The same operation can be achieved using list comprehension too:

Flatten a list of DataFrames

For flattening a list of DataFrames, the pandas library has a built-in function for flattening called df.concat() Let’s take a look at code:

Flatten & remove duplicates

First, we will flatten our list, then we will remove the duplicates.

For flattening the list, we will use our own flatten_without_rec() function, and then we will remove the duplicates.

Let us have a look at the code:

Flatten a dictionary into a list

You can flatten a dictionary to a list using a simple for loop:

Let us have a look at the code:

Using reduce

The reduce() function is defined in the functools library. You first need to import reduce from the functools.

Let’s take a look at the code:

We flattened lists with different shapes & types in different ways. I hope you find the tutorial useful. Keep coming back.

Thank you.